TransNetV2 Scene Detect
SkillMediaTransNetV2-based video scene detection skill. Use when a task needs high-accuracy shot boundary detection, local scene splitting, or downstream video-analysis workflows that depend on the TransNetV2 pipeline.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the TransNetV2 Scene Detect skill
What this skill tells your AI
The instructions your AI receives, as published by qianleigood/crawclaw in skills-optional/transnetv2-scene-detect/SKILL.md and read by ahel’s review.
Use this as the default high-accuracy scene detection path.
Use this skill for
- scene boundary detection
- local video preprocessing and cutting
- generating shot JSON outputs
- supporting
video-analysis-workflow
Default workflow
- Use
run.shfor the main entry path. - Ensure weights exist at the expected asset path.
- Write outputs into
output/, not the skill root. - Keep script names and asset paths stable unless downstream references are updated too.
Read references as needed
references/README.mdFor historical notes, structure background, and migration details.
Working rules
- Treat
output/as runtime artifacts, not source. - Treat
archive/as history, not active guidance. - Do not casually move scripts, weights, or directory layout while
video-analysis-workflowdepends on them.
Signals
- GitHub stars
- 30
- Forks
- 1
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
transnetv2-scene-detect- Source
- github.com/qianleigood/crawclaw